How to interpret SQL Server deadlock graphs

24 Oct 2023

When working with SQL Server, it’s important to understand and analyze deadlock graphs to identify and resolve concurrency issues. Deadlocks occur when two or more processes are waiting for each other to release resources, resulting in a deadlock situation.

Fortunately, SQL Server provides a mechanism for capturing and analyzing deadlock graphs, which can help pinpoint the cause of the deadlock and suggest possible solutions. In this blog post, we will explore how to interpret SQL Server deadlock graphs and use them to troubleshoot and resolve deadlocks.

Enabling deadlock graph capture

Before we dive into interpreting the deadlock graphs, let’s first ensure that deadlock graph capture is enabled in SQL Server. By default, deadlock graphs are not captured, so we need to enable this feature.

To enable deadlock graph capture, execute the following command in SQL Server Management Studio:

DBCC TRACEON(1222, -1)

This command activates trace flag 1222, which enables the capture of deadlock information in the SQL Server error log.

Analyzing deadlock graphs

Once deadlock graph capture is enabled, SQL Server will generate a trace flag event whenever a deadlock occurs. The deadlock graph contains valuable information about the processes involved, the resources they are waiting for, and the statements that caused the deadlock.

To analyze a deadlock graph, you can use various tools such as SQL Server Management Studio, SQL Profiler, or querying the system_health extended event session.

The deadlock graph is represented in an XML format, which can be accessed using the following query:

SELECT
    event_data
FROM
    sys.fn_get_audit_file('<path to the error log file>', null, null)
WHERE
    event_type = 'xml_deadlock_report'

Once you have retrieved the deadlock graph XML, you can open it in a tool capable of parsing XML files or use an online XML parser to make it more readable.

Interpreting deadlock graphs

When interpreting a deadlock graph, there are several key elements to pay attention to:

Victim process: The victim process is the process chosen by SQL Server to be terminated and resolve the deadlock. It’s important to analyze why this process was chosen and whether it can be prevented.
Process nodes: Each process involved in the deadlock is represented as a process node in the graph. These process nodes provide information about the session ID, transaction ID, and the statements being executed at the time of the deadlock.
Resource nodes: Resource nodes represent the resources that the processes are waiting for. These can be locks on individual rows, pages, or entire tables. Analyzing the resource nodes can help identify the cause of the contention.
Edge tags: The edges connecting the process and resource nodes provide additional information about the relationship between them. They indicate which process is waiting for which resource and vice versa.

By examining the process nodes, resource nodes, and edge tags in the deadlock graph, you can gain insights into the root cause of the deadlock. This information can guide you in making changes to the database schema, queries, or application logic to prevent future deadlocks from occurring.

Resolving deadlocks

Once you have analyzed the deadlock graph and identified the cause of the deadlock, you can take steps to resolve it. Here are some common approaches:

Optimize the queries: Analyze the queries involved in the deadlock and look for opportunities to optimize them. This can include adding indexes, rewriting queries, or reordering statements to minimize contention.
Adjust isolation levels: Consider adjusting the isolation levels of the transactions involved in the deadlock. Choosing a lower isolation level can reduce the likelihood of deadlocks but may compromise data consistency.
Implement row versioning: In SQL Server, enabling row versioning can help mitigate deadlocks by using row versioning instead of locks for read operations.
Use lock hints: Applying lock hints in your queries can help control the locking behavior and potentially avoid deadlocks. However, this approach should be used judiciously, as it can have unintended consequences.
Implement retry logic: If deadlocks are infrequent and resolving them is not critical, you can implement retry logic in your application to automatically retry the failed transaction after a short period.

Conclusion

Interpreting SQL Server deadlock graphs is essential for troubleshooting and resolving deadlocks. By enabling deadlock graph capture, analyzing the graphs, and implementing appropriate solutions, you can minimize the occurrence of deadlocks and improve the overall performance and stability of your SQL Server environment.

References: